I am a soon-to-be graduate student with three years of professional experience. Not your typical new graduate, I have specifically sought to work with small-sized companies and place myself in challenging situations to rapidly learn a wide range of diverse skills and grow as an individual.

Taking two years between my B.Sc. and M.Sc. program assured me that working in information technology and data was the right career path. During this time, I became a regular at data science meetups, developed strong work habits, and learned deep learning architectures in my free time. I was involved in all other aspects of data science outside of the core modeling and analytical work, including managing data privacy, software lifecycle/version control, and presentations/managing clients. Despite my short tenure, I became the go-to problem solver for database optimization, automation, and handling unstructured messy data.

After this short break from study, I decided to pursue an M.Sc. in Data Science, an idea that had taken root in the final years of my undergrad. I planned to study abroad, in a new environment, with new challenges. I flew to Maastricht, a small town in the southern province of the Netherlands, having never even stepped foot in Europe in my life. For me, the value of the additional study is and always will be on personal growth.

Once in Maastricht, I was able to adapt quickly to each challenge I was presented. In addition to my regular course load, I got into the best shape of life, held down multiple teaching assistant positions, and got my first research paper accepted into the Educational Data Mining conference.

I am currently working in health care, writing my thesis, managing software regulations, working in development sprints, and coordinating model development with physicians. In addition to this, I am designing adaptive and robust algorithms for saving energy in intelligent homes and writing scripts to extract chemical compound information to expand WikiData.